Study Design
Start with Clear Objectives
Before creating a study, articulate:- The core question: What must this research answer?
- The decisions: What will you do differently based on what you learn?
- The stakeholders: Who needs to act on these insights?
Focus on Depth, Not Breadth
Don’t try to cover everything. Studies that go deep on 4-6 topics deliver more actionable insights than broad studies that skim 15 topics.Write for Your Participants
Use language your participants actually use, avoid internal jargon and acronyms, and frame questions from their perspective rather than your org chart’s. Good questions invite a story rather than a yes or no:
The pattern: ask about what happened, not what someone thinks or would do. People are poor at predicting themselves and good at recounting what they did.
Trust the AI to Probe
You don’t need to script every follow-up question. The AI interviewer naturally:- Asks “tell me more” when responses are brief
- Probes deeper when participants mention something interesting
- Requests specific examples to ground abstract statements
- Follows unexpected threads that may reveal insights
Participant Recruitment
Match the audience to the question
When the question is about your product — why they churned, what confused them in onboarding, whether the new pricing lands — interview your own participants. They bring real experience with the thing you’re asking about, and their feedback is specific rather than hypothetical. Use the research panel when you need people who aren’t your customers: category research, competitive work, or testing a concept with a market you haven’t reached yet.Set Clear Expectations
In your invitation, communicate:- How long the interview will take (be accurate)
- What topics you’ll cover (high level)
- Why their feedback matters
- Any incentives offered
Time Your Invitations
Send Reminders
A single reminder 3-5 days after the initial invitation can significantly improve response rates. Keep it brief and friendly.Watch for self-selection
Anyone can follow an open study link, and the people who volunteer are rarely a neutral sample — they tend to be your most enthusiastic or most annoyed customers, with the quiet middle missing. That’s fine when you want strong opinions; it’s a problem when you want a representative read. Use screeners to keep the wrong people out, and reach for the panel when representativeness matters.During Data Collection
Monitor Early Responses
Listen to your first 3-5 interviews to:- Confirm questions are understood correctly
- Verify the conversation flows naturally
- Catch any issues before scaling recruitment
- Validate your research hypotheses (or adjust them)
Don’t Edit Mid-Study
Once participants have started completing interviews:- Avoid changing questions (compromises comparability)
- Don’t adjust the flow (earlier and later responses won’t match)
- Note issues for next time instead of fixing mid-stream
Check Quality Distribution
Monitor your Quality count relative to total responses. If too many interviews come back Fair or Poor:- Review if questions are confusing
- Check if you’re reaching the right participants
- Consider whether the topic engages participants
Analysis and Reporting
Look for Patterns, Not Just Quotes
Individual quotes are powerful, but patterns matter more:- What do multiple participants mention?
- Where do responses contradict each other?
- What’s notably absent from conversations?
Separate strong signals from weak ones
Strong — mentioned by several participants, consistent across segments, and backed by specific examples rather than generalities. Weak — one participant, contradicted elsewhere, or asserted without an example behind it. Weak signals aren’t worthless; they’re hypotheses for the next study rather than findings for this one.Treat contradictions as information
When participants disagree, the disagreement is usually the finding. Look for a segment difference behind it — new versus long-term, one plan versus another, one market versus another. A contradiction that splits cleanly along a segment line is a discovery. One that doesn’t usually means you need more interviews.Spot-check before you share
Follow a few quotes back to their transcripts before a report goes to stakeholders. It takes minutes, it catches the occasional quote that reads differently in context, and it means you can answer “where did this come from?” in the meeting.Consider Sample Size
How much your sample supports depends on how common the thing you’re looking for is. Five interviews is plenty for something half your users hit and close to a coin flip for anything affecting 1 in 10. Work out what your number actually buys — and how many you’d need for the confidence you want — with the sample size calculator. Always state your sample size when sharing findings, and state it per segment if you split the sample.Connect Insights to Actions
Every insight should connect to potential action:
If an insight doesn’t connect to a potential action, consider whether it was worth learning.
Share Widely, But Appropriately
Building a Research Practice
Create Recurring Studies
For ongoing intelligence, establish:- Quarterly brand tracking — the same questions to a fresh sample each quarter
- Monthly churn research — talk to people shortly after they leave
- Continuous onboarding feedback — via the embed widget
- Post-launch research for each major release
Build Institutional Knowledge
User Intuition’s Intelligence Hub becomes more valuable over time:- Query across historical studies
- Identify long-term trends
- Preserve knowledge through team changes
- Accelerate onboarding for new team members
Close the Loop
After each study:- Share findings with stakeholders
- Identify 2-3 concrete actions
- Track whether actions were taken
- Measure impact where possible
- Document learnings for future studies
Common Mistakes to Avoid
Asking leading questions
Asking leading questions
❌ “Don’t you think our checkout is confusing?”
✅ “Walk me through your experience with checkout.”
✅ “Walk me through your experience with checkout.”
Covering too many topics
Covering too many topics
❌ 20 topics in a 15-minute interview
✅ 5-6 topics explored deeply
✅ 5-6 topics explored deeply
Ignoring low-quality responses
Ignoring low-quality responses
Low-quality responses often reveal confusion or disengagement—which is itself a finding worth investigating.
Over-indexing on single responses
Over-indexing on single responses
One passionate participant doesn’t make a pattern. Wait for consistent themes across multiple interviews.
Researching without acting
Researching without acting
Research that doesn’t lead to action wastes resources and erodes organizational trust in research value.
Editing studies mid-collection
Editing studies mid-collection
Resist the urge to tweak questions once interviews have begun. Note improvements for next time instead.
Quick Reference
Study Setup Checklist
- Clear research objective defined
- 4-6 focused topics identified
- Questions written in participant language
- Decision/action identified for insights
- Study tested before launch
Recruitment Checklist
- Target participants identified
- Invitation includes time estimate
- Incentive communicated (if applicable)
- Reminder plan in place
- Early responses monitored
Analysis Checklist
- Listened to sample of interviews (not just read transcripts)
- Patterns identified across multiple participants
- Sample size noted with findings
- Insights connected to actions
- Appropriate sharing with stakeholders